摘要
针对视频图像序列中人脸关键点跟踪对鲁棒性和实时运行的要求,提出一种新的人脸关键点实时跟踪方法。运用光流法跟踪若干显著关键点,为下一帧选择更好的初始形状,根据当前帧的人脸形状估计下一帧的人脸框,以减少对人脸检测器的依赖,同时为防止误差累积,加入人脸检测器重启机制。实验结果表明,该方法在300-VW数据集上实现了68个人脸关键点的鲁棒跟踪,运行速度达30+f/s,可用于大多数人脸相关的实时应用。
Aiming at the requirement of robustness and real-time running of facial key point tracking in video sequence,this paper proposes a simple and effective real-time tracking method of facial key points.The optical flow method is used to track a number of significant points and select a better initial shape for the next frame.The face frame of the next frame is estimated according to the face shape of the current frame to reduce the dependence on the face detector.To prevent errors accumulation,the face detector restart mechanism is joined.Experimental results on a 300-VW dataset show that this method can achieve robust tracking of 68 face key points with a speed of 30+f/s,which can be used for most face real-time applications.
作者
徐威威
李俊
XU Weiwei;LI Jun(School of Information Science and Technology,University of Science and Technology of China,Hefei 230027,China)
出处
《计算机工程》
CAS
CSCD
北大核心
2018年第4期281-286,共6页
Computer Engineering
关键词
人脸关键点
局部二值特征
显著关键点
初始形状
光流
facial key point
Local Binary Feature(LBF)
significant key point
initial shape
optical flow
